code: def test_big_prime_number_sum(self):
      a = Tensor.rand(367, 367)
      b = Tensor.rand(367, 367)
      # if incorrectly padded 0, the sum would be inf
      c = (a / b).sum(1).realize()
      np.testing.assert_allclose(
          c.numpy(),
          (a.numpy() / b.numpy()).sum(1),
          atol=1e-4,
          rtol=1e-4,
      )
  
file_path: tinygrad/extra/optimization/test_beam_search.py
imports: import unittest
  import numpy
  from tinygrad.helpers import BEAM, Timing
  from tinygrad.shape.symbolic import Variable
  from tinygrad.tensor import Tensor
  from tinygrad.nn import Conv2d
label_desc: Use image node_id 6 for calling the TestBeamSearch obj's underlying member method code with example usage: obj.test_big_prime_number_sum() without return types